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Pangram

Pangram (formerly Checkfor.ai) is an AI-text detector that estimates how likely writing was AI-generated, used by schools, publishers, and institutions.

Known aliases

  • Checkfor.ai
  • Pangram 4
  • Pangram Labs
  • Pangram v3.3

Relationships

No evidence-backed relationships are recorded.

Current stories

product3 publishers

France's Goncourt dropped a likely-AI novel once plagiarism reports gave it a second reason

France's Académie Goncourt dropped Thélyson Orélien's novel from its first selection, citing plagiarism and analyses that AI most likely wrote most of it. For anyone who sells AI checks, the case shows a likelihood score counting once a plagiarism record sat beside it.

Perspective Coverage

3 publishers
Builder
Builder 35%
Operator
Operator 48%
Investor
Investor 17%

Reality

Evidence58
Adoption
Insufficient
Hype gap+20
Incentives55
Confidence60
build6 publishers

Anthropic's Watermark Answers The Wrong Question, And Its Own Docs Say So

The Claude watermark survives light editing and dissolves under heavy editing, and its absence proves nothing. Policies that treat it as a verdict are built on a binary that does not exist.

Perspective Coverage

6 publishers
Builder
Builder 42%
Operator
Operator 45%
Investor
Investor 13%

Reality

Evidence60
Adoption50
Hype gap+15
Incentives50
Confidence60
product7 publishers

Claude's watermark is an EU compliance artifact, and it lands on undisclosed output

Anthropic says it is watermarking Claude text to satisfy the EU AI Act Transparency Code and plans a detection API. The exposure sits with teams shipping generated work as their own.

Perspective Coverage

7 publishers
Builder
Builder 37%
Operator
Operator 44%
Investor
Investor 19%

Reality

Evidence48
Adoption45
Hype gap+20
Incentives62
Confidence55
product3 publishers

Nairobi's essay trade now sells detector evasion instead of essays

Researchers counted at least 40,000 people in Nairobi writing other people's coursework early this decade. The trade is close to gone, and the work that still pays is rewriting model output by hand until the software cannot tell.

Perspective Coverage

3 publishers
Builder
Builder 20%
Operator
Operator 50%
Investor
Investor 30%

Reality

Evidence55
Adoption40
Hype gap+25
Incentives30
Confidence60
build8 publishers

Malicious gems used RubyDoc.info's build workers to crawl UK government pages

Three of the four authors of last week's wiki-agent report say an OpenAI swarm very likely published the hundreds of packages that hit RubyGems on 12 May, and their strongest evidence is a retrieval trick the wiki agents also used.

Publishers:dev.tomend.iomezha.netrubyhack.airuntimewire.comsimonwillison.netthe-decoder.comwhtc.com

Perspective Coverage

8 publishers
Builder
Builder 36%
Operator
Operator 39%
Investor
Investor 25%

Reality

Evidence70
Adoption
Insufficient
Hype gap+20
Incentives55
Confidence65

Earlier coverage

  1. A five-hour script beats Claude's watermark, so stop treating it as provenance

    Product · August 19, 2026 · 3 publishers

  2. The AI writing policy is a coordination cost showing up on the wrong line item

    Invest · August 19, 2026 · 1 publisher

  3. The AI book problem is arithmetic: catalog up 38x, revenue up 9x

    Build · August 15, 2026 · 1 publisher